IEEE

Mask Optimization for Image Inpainting Using No-Reference Image Quality Assessment

Abstract: Image inpainting is a technique designed to remove unwanted regions from images and restore them. This technique is expected to be applied in various applications, including image editing, ...
IEEE

Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints – Optimization and Machine Learning Design

Abstract: Reconfigurable intelligent surfaces (RISs) are an emerging technology for improving spectral efficiency and reducing power consumption in future wireless systems. This paper investigates the ...
IEEE

A Novel CNN Architecture for Alzheimer's Disease Classification Using MRI Images: Comparison with Traditional Machine Learning Models

Abstract: Automated medical image processing has significantly improved with recent advances in deep learning and imaging technologies, particularly in the area of neuroimaging-based Alzheimer's ...
IEEE

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
IEEE

3D Semantic Segmentation of Airborne & UAV LiDAR Point Clouds for Precise Tree Counting: a Machine Learning Approach

Abstract: In a world where sustainable forest management and understanding of our ecosystems have become priorities, accurately and efficiently counting trees, especially in geographically challenging ...
IEEE

Latest Trends in Face Recognition using CNN

Abstract: Face Recognition is a computer vision technology that identifies or verifies a person’s identity using a person’s facial features. It is widely used in different fields like security, ...
IEEE

SegMamba-V2: Long-range Sequential Modeling Mamba For General 3D Medical Image Segmentation

Abstract: The Transformer architecture has demonstrated remarkable results in 3D medical image segmentation due to its capability of modeling global relationships. However, it poses a significant ...
IEEE

A Transfer Learning Approach for Landslide Semantic Segmentation Based on Visual Foundation Model

Abstract: Landslides are one of the most destructive natural disasters in the world, threatening human life and safety. With excellent performance as a foundation model for image segmentation, the ...
GitHub

Mask R-CNN Instance Segmentation with OpenCV

This project demonstrates instance segmentation using Mask R-CNN with the OpenCV DNN module. The model is pre-trained on the COCO dataset and can detect and segment multiple object classes in images.
IEEE

Machine Learning-based Customer Segmentation with Optimal Cluster Selection

In Algorithms for Machine Learning Before applying modern clustering algorithms, data was analyzed using rulebased grouping, eye scanning, manual computation of distances, and hierarchical sorting, ...
IEEE

A Semi-supervised Ultrasound Image Segmentation Network Integrating Enhanced Mask Learning and Dynamic Temperature-controlled Self-distillation

Abstract: Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is often degraded by speckle noise, low ...
IEEE

Improving Cell Nuclei Segmentation in Pathological Tissues Using Self-Supervised Regression Method

Abstract: Digital pathology, integral to cancer diagnosis, heavily utilizes the analysis of whole slide images (WSIs) to detect cancer cells. Traditionally, WSIs are manually examined—a process that ...